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COMMENTARY AND DISCUSSION ARTICLE
Digesting the alphabet soup of LCA
Jeroen B. Guinée1 & Stefano Cucurachi1 & Patrik J.G. Henriksson2& Reinout Heijungs1,3
Received: 13 March 2018 /Accepted: 24 April 2018 /Published online: 23 May 2018# The Author(s) 2018
Keywords Attributional LCA . Consequential LCA . Explorative LCA .Modes of LCA .Modelling
1 Introduction
One of the most pertinent and enduring debates within the life-cycle assessment (LCA) community is on consequential(CLCA) and attributional LCA (ALCA), see for example,Weidema et al. (1999), Guinée et al.(2002), Ekvall andAndræ (2006), Schmidt (2010), Zamagni et al. (2012), Rehlet al. (2012), Anex and Lifset (2014), Brandão et al. (2014),Suh and Yang (2014), Dale and Kim (2014), Hertwich (2014),Plevin et al. (2014a), Plevin et al. (2014b), Ekvall et al. (2016),and Weidema et al. (2018). Amongst other things, the debatefocuses on similarities and differences between these twomodes and on which mode is more appropriate for which caseor question. Some authors claimed superiority of one of thesemodes over the other (Plevin et al. 2014a; Weidema et al.2018). Here, we refrain from further dwelling on this dis-cussion, but rather discuss the more recent emergence ofother modes of LCA. These new modes have been devel-oped by independent scholars, outside the ISO standards(International Organization for Standardisation 2006) and
outside national and continental guidelines (e.g., EuropeanCommission—Joint Research Centre—Institute forEnvironment and Sustainability 2010). They all focus onestimating life-cycle impacts of future systems and we ar-gue that they are all varieties of analysis fitting under theumbrella of Bexplorative^ LCA. To substantiate this, wefirst look into the definitions of ALCA, CLCA, and someof the newer modes of LCA. We then briefly discuss sim-ilarities and differences between these different LCAmodes, and conclude that rather than discussing differentmodes, the LCA community should focus on discussingtheir underlying real differences.
Responsible editor: Mary Ann Curran
* Jeroen B. Guiné[email protected]
1 Institute of Environmental Sciences (CML), Department of IndustrialEcology, Leiden University, Einsteinweg 2, 2333CC Leiden, The Netherlands
2 Stockholm Resilience Centre, Stockholm University,10691 Stockholm, Sweden
3 Department of Econometrics and Operations Research, VrijeUniversiteit Amsterdam, De Boelelaan 1105, 1081HVAmsterdam, The Netherlands
The International Journal of Life Cycle Assessment (2018) 23:1507–1511https://doi.org/10.1007/s11367-018-1478-0
2 Panoply of definitions
A widely used set of definitions for ALCA and CLCA wasprovided in the UNEP report on BGlobal Guidance Principlesfor Life Cycle Assessment Databases^ (UNEP 2011):
& Attributional LCA (ALCA): to provide information onwhat portion of global burdens can be associated with aspecific product life cycle.
& Consequential LCA (CLCA): to provide information onthe environmental burdens that occur, directly or indirect-ly, as a consequence of a decision (usually represented bychanges in demand for a product).
In the recent LCA literature, we can findmanymoremodesof LCA. Below, we list these other modes of LCA and providea brief definition:
& Backcasting LCA (BLCA): exploring ways—in a life-cycle perspective—to meet normatively defined sustain-ability levels (planetary boundaries) through adapted af-fluence (as consumption levels), population growth, and/or technologies (Heijungs et al. 2014);
& Decision LCA (DLCA): based on CLCA but using theactual or anticipated financial and contractual relationsbetween economic actors (business-to-business relations)as the main basis of information (Frischknecht 1998;Frischknecht and Stucki 2010);
& Integrated LCA (ILCA): LCA integrated with othermodeling approaches such as input-output analysis,
energy-scenario modeling, and, for example, materialflow analysis (Hertwich et al. 2014); method for assessingthe environmental and resource implications of scenariosfor large-scale adoption of climate changemitigation mea-sures (Gibon et al. 2015);
& Anticipatory LCA (NLCA): a forward-looking, non-predictive tool that increases model uncertainty through in-clusion of prospective modeling tools, decision theory, andmultiple social perspectives (Wender et al. 2014);
& Prospective LCA (PLCA): estimating future life-cycle en-vironmental impacts using scenarios (Spielmann et al.2005; Walser et al. 2011);
& Scenario-based LCA (SLCA): LCA based on scenariosseparating three modeling processes, life-cycle modeling,scenario modeling, and valuation modeling (Fukushimaand Hirao 2002).
Perhaps, there are a few more varieties that we missed. Butthe conclusion is clear: an alphabet soup of LCA modes hasemerged. The big question is of course: what is their relation?
3 Similarities and differences
ALCA is the only mode focusing on modeling a situation as itis, either in the past, present, or future, but without any chang-es. The other modes, from BLCA up to SLCA, have a lot incommon. They all aim at estimating the effects of changedsituations, where the change and/or the background state arebased on a scenario.
Table 1 Examples of questionsaddressed by different modes ofLCA
Question Reference
ALCA What is the life-cycle impact of 1 kWh of electricity atgrid in France in 2006?
(Frischknecht and Stucki 2010)
BLCA What is the maximum attainable affluence for the EU27in 2020 and 2050 to meet related EU GHG target?
(Heijungs et al. 2014)
CLCA What are the consequences of an increased demandof wheat in Denmark?
Which effect does the decision to purchase anadditional kWh of electricity have on the electricitymarket and/or on the environmental impacts?
(Schmidt 2010)
(Frischknecht and Stucki 2010)
DLCA Which effect does the decision to purchase anadditional kWh of electricity have on the electricitymarket and/or on the environmental impacts?
(Frischknecht and Stucki 2010)
ILCA What are the system-wide life-cycle impacts of aspecific energy transition?
(Hertwich et al. 2014)
NLCA What are the future environmental burdens associatedwith an emerging technology for both reasonableand extreme-case scenarios?
(Wender et al. 2014)
PLCA What are the environmental benefits and impactsof nanosilver T-shirts compared with conventionalT-shirts and T-shirts treated with triclosan?
(Walser et al. 2011)
SLCA What is the best scenario for improving the life-cycleenvironmental performance of a car?
(Fukushima and Hirao 2002)
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Table2
Key
characteristicsof
modes
ofLCA
Questionaddressed
Key
method
Objecto
fanalysis
Scope
Other
methods/m
odels
used
Allo
catio
nmethod
Temporal
Processes
Data
ALCA
Whatare
theenvironm
ental
impactsof
aproductsystem
asitcurrently
functio
ns?
LCA
Com
mercially
existin
gproductsystem;asit
isor
was
Present,past
All
SDb
n.a.
Variable
BLCA
Whatisaregion’smaxim
umattainableaffluenceto
meet
itsplanetaryboundaries
attim
etw
ithconstant
technologies
andpopulatio
n?
IOA
Regional/g
lobalconsumption;
asitshould
beFu
ture,past
Allsectors
Linearprogramming(LP)
simplex
algorithm
Variable
CLCA
Whatare
theconsequences
ofan
increaseddemandof
acertainproductsystem?
LCA
Com
mercially
existin
gproductsystem;asit
changesdueto
adecision
Future
Marginal,market
SDb
CGEM;P
GEM;IAM;
LOM
Substitution
DLCA
Whatare
theconsequences
ofan
increaseddemandof
acertainproductsystem?
LCA
Com
mercially
existin
gproductsystem;asit
changesdueto
adecision
Future
Marginal,B2B
SDb
n.a.
Substitution
ILCA
Whatare
thegloballife-cycle
impactsof
aspecificenergy
transitio
n?
LCA
Globalenergyconsum
ption
Future
All
SDbandTI,
B,IOA
IOA,IEABlueMap
scenario
Variable
NLCA
Whatare
theexpected
environm
entalimpacts
ofan
emerging
product
system
?
LCA
Emerging
productsystem
Future
All
SDbandTI,
F,B(optional)
Learningcurves;technology
andchem
icalmodels
Variable
PLCA
Whatare
theexpected
environm
entalimpacts
ofan
emerging
product
system
?
LCA
Emerging
productsystem
Future
All
SDbandTI,
F,B(optional)
Learningcurves;technology
andchem
icalmodels
Variable
SLCA
Whatare
theexpected
environm
entalimpacts
ofacertainfuture
scenario
ofaproductsystem?
LCA
Emerging
productsystem
Dynam
ic,
from
past
tofuture
All
Calculated
Life-cyclemodeling
language
Variable
n.a.notapplicable;productsystem
(ortechnologysystem
)asetofunitprocessesinterlinkedby
material,energy,product,w
aste,orservice
flow
sandperformingoneormoredefinedfunctio
ns(G
uinéeetal.
2002);SD
bstandard
LCAdata(bases),such
asecoinvent,GaB
i,ILCD,and
USD
A;T
Iassum
ptions
ontechnicalimprovem
entsinkeyenergy
andmaterialproductiontechnologies
(Hertwichetal.2014);F
foreground
processes;Bbackground
processes;CGEM
computableandpartialgeneralequilib
rium
model;PGEM
partialgeneralequilib
rium
model;IAM
integrated
assessmentmodel;LO
Mlin
ear
optim
izationmodel;A
llallprocesses
included
forsupplying
thefunctio
nalunit;Allsectorsa
llindustry
sectorsincluded
forsupplying
theregion’s/globalconsumption;Marginalprocesses
actuallyaffected
bythedecision;M
arketaffectedprocessesaredeterm
ined
byusingmarketinformationandpriceelasticities;B
2Baffected
processesaredeterm
ined
byfactualoranticipated
econom
icbusiness-to-business
relatio
nship
Int J Life Cycle Assess (2018) 23:1507–1511 1509
There are of course also differences between these modesregarding questions addressed (see Table 1 for some selectedexamples from literature), objects of analysis, processes in-volved, object of analysis, temporal scope, processes covered,data scope, additional methods and models adopted, and allo-cation methods used; see Table 2 for a summary of similaritiesand differences.
Table 2 shows that one main divide between modes con-cerns the object of analysis. Some modes mainly focus oncommercially existing product systems (ALCA, CLCA,DLCA), while other modes focus on emerging, novel, andnot yet marketed product systems (NLCA, PLCA, SLCA).Next, Table 2 shows that all modes except ALCA aim to assessthe environmental life-cycle performance of a future system onthe short, mid, or long term. CLCA then becomes just onemode out of at least six other modes to model life-cycle impactsof possible consequences of changes to existing product sys-tems, or of introducing novel technology or product systems.Depending on the exact question posed, one of these sixmay bepreferred, but we might also want to apply all of them and seehow robust LCA results are for different assumptions that aredifficult to verify or falsify (Yang and Heijungs 2018).
Another fundamental difference concerns the data require-ments of the different modes: standard databases without anychanges or standard databases with changes based on assumedtechnological improvements, supplemented by new datasetsfor foreground processes. As process data are one of the maindrivers of final LCA results, differences at this level may havea huge effect on results.
Finally, Table 2 shows that by focusing the discussion ondifferences between modes, we may overlook the fact thatthere are also some fundamental modeling differences withinone mode. This was recently exemplified for CLCA and ar-gued to be potentially more important than differences be-tween modes (Yang and Heijungs 2018). In addition,Table 2 shows comparable differences within NLCA andPLCA (see column Bother methods/models used^).
4 Conclusions
Over the past decade, an alphabet soup of modes of LCAs hasemerged. This soup of LCA modes can be split into two maingroups: ALCA is the only mode focusing on modeling a sit-uation as it is, either in the past, present, or future, but withoutany changes. We suggest classifying the group of BLCA-ZLCA as life-cycle modeling of the unknown by exploringscenarios of potential futures, or shortly Bexplorative LCA.^Let us call them XLCA, where X ∈ {B,C,…, Z}, and more-over X codes for eXplorative.
Eachmode of LCA has its merits and demerits and we haveshown that they share many similarities despite also some
differences. In addition, we have shown that the methodsand models used in combination with the key method (i.e.,mostly LCA) may widely vary. Therefore, based on an anal-ysis of similarities and differences between the differentXLCA modes, we conclude that rather than discussing differ-ent modes, the LCA community should focus on discussingthe underlying differences including the object of analysis,other methods/models used in combination with the key meth-od, data, and scenarios adopted. Our starting position in thisdebate is that instead of distinguishing BLCA-ZLCA as dif-ferent modes of XLCA, we actually have a multi-model multi-paradigm approach within the group of XLCA (Yang andHeijungs 2018). Different questions posed will need differentmodels and approaches and probably not just one model andone approach but rather a suite of applicable models and ap-proaches. Selecting single models and approaches for specificquestions may be a bridge too far. All models rely on strongassumption and constraints, and as LCA outcomes are largelyunverifiable (Guineé et al. 2017; Yang and Heijungs 2018),claiming certain LCA modes or models to be superior cannotbe supported by evidence, and this battle between schools isthus a dead-end in our view.
We strongly recommend that explorative LCA studies fromhere on explicitly formulate their research questions and ob-ject of analysis and justify other models, data, and scenariosselected on the basis of these questions and objects.We expectthat the latter will help advance the debate on how differentapproaches, modes, and models may best support certainquestions and decisions, which is a research topic on whichlittle progress has been achieved so far.
We would like to conclude by paraphrasing Suh and Yang(2014): BDividing the LCA world into CLCAs and ALCAsoverlooks the studies^ not fitting this divide and Bhampers aconstructive dialog about the creative use of modellingframeworks.^
Open Access This article is distributed under the terms of the CreativeCommons At t r ibut ion 4 .0 In te rna t ional License (h t tp : / /creativecommons.org/licenses/by/4.0/), which permits unrestricted use,distribution, and reproduction in any medium, provided you give appro-priate credit to the original author(s) and the source, provide a link to theCreative Commons license, and indicate if changes were made.
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